# *python-cartogram* - compute continuous cartograms


:::{figure} _static/images/Austria_PopulationCartogram_NUTS2_20170101.svg
:alt: A map showing the nine federal provinces of Austria, distorted in a way that their relative areas relate to their population numbers.
:class: align-default

The nine federal provinces of Austria, distorted so their area sizes match their population numbers
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% -> https://github.com/sphinx-contrib/images/pull/39#issuecomment-2258779386

% :::{thumbnail} _static/images/Austria_PopulationCartogram_NUTS2_20170101.svg
% :alt: A map showing the nine federal provinces of Austria, distorted in a way that their relative areas relate to their population numbers.
% :title: The nine federal provinces of Austria, distorted so their area sizes match their population numbers
% :show_caption: 1
% :class: align-default
% :::


**python-cartogram** is a Python package that can be used to compute continuous
cartograms. These map-like cartographic visualisations, also known as
*anamorphic maps*, show areal features distorted by an attribute value, for
instance census tracts resized by population size, or election districts by
voter counts. Learn more about anamorphic maps
[here](https://austromorph.space/anamorphic-maps/).

The package is modelled after the [QGIS plugin
*cartogram3*](https://github.com/austromorph/cartogram3). Just like it,
**python-cartogram** implements the iterative, approximating algorithm by
{cite:t}`dougenik_1985`, but it is designed to seamlessly interact with a
{class}`geopandas.GeoDataFrame`.

:::{toctree}
:caption: User guide
:maxdepth: 1
:hidden:

installation
quickstart
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:::{toctree}
:caption: API reference
:maxdepth: 1
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Module contents <reference>
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